Skip to main content

Optimization Test Problems

Welcome, Anonymous

The following test libraries are routinely used in the context of developing BARON. Some of these problems originate from applications, while others have been designed to test, develop, or challenge solvers:


Sources:

  1. Bao, X., N. V. Sahinidis, and M. Tawarmalani, Multiterm polyhedral relaxations for nonconvex, quadratically-constrained quadratic programs, Optimization Methods and Software, 24, 485-504, 2009.
  2. Bao, X., N. V. Sahinidis and M. Tawarmalani, Semidefinite relaxations for quadratically constrained quadratic programming: A review and comparisons, Mathematical Programming, 129, 129-157, 2011.
  3. Bao, X., A. Khajavirad, N. V. Sahinidis, and M. Tawarmalani, Global optimization of nonconvex problems with multilinear intermediates, Mathematical Programming Computation, 7, 1-37, 2015.
  4. Vandenbussche, D. and G. Nemhauser, A branch-and-cut algorithm for nonconvex quadratic programs with box constraints, Mathematical Programming, 102, 559-575, 2005.
  5. Puranik, Y. and N. V. Sahinidis, Deletion presolve for accelerating infeasibility diagnosis in optimization models, INFORMS Journal on Computing, 29, 754-766, 2017.
  6. Sherali, H. D., E. Dalkiran and J. Desai, Enhancing RLT-based relaxations for polynomial programming problems via a new class of v-semidefinite cuts, Computational Optimization and Applications, 52, 483-506, 2012.
  7. Sherali, H. D., E. Dalkiran and L. Liberti, Reduced RLT representations for nonconvex polynomial programming problems, Journal of Global Optimization, 52, 447-469, 2012.
  8. Puranik, Y. and N. V. Sahinidis, Bounds tightening on optimality conditions for nonconvex box-constrained optimization, Journal of Global Optimization, 67, 59-77, 2017.
  9. Cozad, A. and N. V. Sahinidis, A global MINLP approach to symbolic regression, Mathematical Programming, 170, 97-119, 2018.
  10. Lima, R. M. and I. E. Grossmann, On the solution of nonconvex cardinality boolean quadratic programming problems: A computational study, Computational Optimization and Applications, 66, 1-37, 2017.
  11. Nohra, C. J., A. U. Raghunathan and N. V. Sahinidis, Spectral relaxations and branching strategies for global optimization of mixed-integer quadratic programs, SIAM Journal on Optimization, 31, 142-171, 2021.
  12. Zhang, Y., N. Ploskas and N. V. Sahinidis, A novel linear programming presolve technique based on Fourier-Motzkin elimination, forthcoming, 2024.
  13. Kuznetsov, A. and N. V. Sahinidis, Nonconvex optimization problems involving the Euclidean norm, forthcoming, 2024.